Yield and Irrigation Water Productivity of Three Varieties of Buffel Grass (Cenchrus ciliaris L.) in the Southern Coastal Plains of Yemen
Bibliographic record
Abstract
Small stakeholder farmers in southern coastal plains of Yemen as in other Arabian Peninsula countries are fanciers and suffering from shortage of forages mainly during winter season. This study was carried out during three years (2012-2014) at farmers’ fields in the southern coastal plain in Bir Jabir, Lahej in Yemen on loamy-sand soil, to determine the best irrigation water productivity of two exotic and one indigenous (local) accessions of buffel grass (Cenchrus ciliaris L.), cultivated at two farmer fields. Irrigation water has been added by the quantity and dates according to the farmer experience without any intervention of the researcher. The amount of added irrigation water was measured. Statistical analysis emphasized significant differences in the number of tillers per plant, in the forage fresh yield and in the irrigation water productivity (IWP) among buffel grass accessions. The highest number of tillers was recorded at Gayandah whereas the USA accession has showed the lowest one. The average forage fresh yields have reached 230.5, 208.9 and 181.4 kg/ha for Gayandah, USA and local respectively. The average irrigation water productivity (IWP) was 39.1 kg/m3. The significant difference (P = 0.048) was in favor of Gayandah accession which registered the highest IWP (43.7 kg/m3). However, there was no significant difference observed in IWP between USA and the local accession, even though this latter has apparently produced the lowest value (36.2 kg/m3).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".